CN107086923B - Communication network performance index analysis method and device - Google Patents
Communication network performance index analysis method and device Download PDFInfo
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- CN107086923B CN107086923B CN201610087765.2A CN201610087765A CN107086923B CN 107086923 B CN107086923 B CN 107086923B CN 201610087765 A CN201610087765 A CN 201610087765A CN 107086923 B CN107086923 B CN 107086923B
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Abstract
The invention discloses a method and a device for analyzing performance indexes of a communication network, which are used for establishing an operation event library and an index event library, wherein the operation event library comprises target operation events to be analyzed; the index event library comprises target index events to be analyzed; then, recording a target operation event occurring in the operation event library and a target index event occurring in the index event library to obtain an event record table for statistics; calculating the confidence degrees of the target index event and the corresponding target operation event according to the obtained event record table; and finally, determining target operation events related to the target index events according to the obtained confidence degrees. By the scheme, the target operation event related to each target index event can be automatically calculated and analyzed based on the result of automatically counting the occurred events. Compared with the existing mode of judging through experience of operators, the method is more objective, higher in efficiency and better in accuracy, and can greatly reduce labor cost.
Description
Technical Field
The invention relates to the field of communication, in particular to a method and a device for analyzing performance indexes of a communication network.
Background
There are various events in the communication network, and the events include two types, one is an operation event and the other is an index event. An operational event is an operation that affects the network or quality of service; an index event is a network or traffic index change. The attribute of the operation event is an event action, the attribute of the index event is a network or service index, and the index threshold value. The operation events and the index events in the communication network are not isolated, and have certain correlation and causal relationship. However, in the current communication network, after various operation events are executed, some problems may be caused, which are expressed as deterioration of index data, that is, some index events are caused; after the index data is deteriorated, reasons can not be found often, the operation events are unknown, and the judgment can only be carried out through the experience of operation and maintenance personnel, so that the efficiency is low, the judgment accuracy is poor, and the labor cost is high.
Disclosure of Invention
The invention aims to solve the main technical problems of providing a communication network performance index analysis method and a communication network performance index analysis device, and solving the problems of low efficiency, poor accuracy and high labor cost caused by the fact that the existing method can only judge the reason of index deterioration through the experience of operation and maintenance personnel.
In order to solve the above technical problem, the present invention provides a method for analyzing performance indexes of a communication network, comprising:
establishing an operation event library, wherein the operation event library comprises target operation events to be analyzed;
establishing an index event library, wherein the index event library comprises target index events to be analyzed;
recording a target operation event occurring in an operation event library and a target index event occurring in the index event library to obtain an event record table;
calculating the confidence degrees of the target index event and the corresponding target operation event according to the event record table;
and determining target operation events related to the target index events according to the obtained confidence degrees.
In an embodiment of the present invention, calculating the confidence of the occurred index event and the corresponding target operation event according to the event record table includes any one of the following manners:
the first method is as follows: when a certain occurring target index event is calculated, calculating the confidence degrees of the target index event and each target operation event;
the second method comprises the following steps: when a certain occurring target index event is calculated, the support degree of the target index event and each target operation event is calculated;
selecting a target operation event with the maximum support value of the target index event;
and calculating the confidence degree of the target indication event and the target operation event with the maximum support value.
In an embodiment of the present invention, determining the target operation event associated with each target index event that occurs according to the obtained confidence includes:
when the mode I is adopted, aiming at a certain occurring target index event, selecting the confidence coefficient with the maximum value from the obtained confidence coefficients of the target index event;
judging whether the selected maximum confidence value is greater than a preset confidence threshold, if so, judging that the target operation event corresponding to the confidence is associated with the target index event;
when the second mode is adopted, whether the value of the obtained confidence coefficient is greater than a preset confidence coefficient threshold or not is judged for a certain occurring target index event, and if yes, the target operation event corresponding to the confidence coefficient is judged to be associated with the target index event.
In an embodiment of the present invention, the target operation event includes at least one of network element version upgrade, network parameter adjustment, load balancing, energy saving setting, and neighbor cell adjustment.
In an embodiment of the present invention, the target indicator event includes at least one of a decrease in handover success rate, an increase in call drop rate, a decrease in access success rate, traffic channel congestion, a decrease in voice quality, and a decrease in data traffic quality.
In order to solve the above problem, the present invention further provides a communication network performance index analyzing apparatus, including:
the operation event library establishing module is used for establishing an operation event library, and the operation event library comprises target operation events to be analyzed;
the system comprises an index event library establishing module, a target analysis module and a target analysis module, wherein the index event library establishing module is used for establishing an index event library, and the index event library comprises target index events to be analyzed;
the event recording module is used for recording a target operation event occurring in the operation event library and a target index event occurring in the index event library to obtain an event recording table;
the calculation module is used for calculating the confidence degrees of the target index event and the corresponding target operation event according to the event record table;
and the analysis module is used for determining target operation events related to the target index events according to the obtained confidence degrees.
In one embodiment of the invention, the calculation module comprises:
the first calculation submodule is used for calculating the confidence degrees of a certain occurring target index event and each target operation event when the certain occurring target index event is calculated;
or comprises the following steps:
the support degree operator module is used for calculating the support degree of a target index event and each target operation event when calculating the target index event;
the support degree selection submodule is used for selecting a target operation event with the maximum support degree value of the target index event;
and the second calculation submodule is used for calculating the confidence degree of the target indication event and the target operation event with the maximum support value.
In one embodiment of the invention, the analysis module comprises:
the confidence degree selection submodule is used for selecting the confidence degree value with the maximum value from the obtained confidence degrees of a certain occurring target index event when the calculation module comprises the first calculation submodule;
the first judgment submodule is used for judging whether the selected maximum confidence value is greater than a preset confidence threshold, if so, judging that a target operation event corresponding to the confidence is associated with the target index event;
or the like, or, alternatively,
the analysis module comprises a second judgment sub-module, and is used for judging whether the obtained confidence coefficient value is greater than a preset confidence coefficient threshold or not when the calculation module comprises a second calculation sub-module, and if so, judging that the target operation event corresponding to the confidence coefficient is associated with the target index event.
In an embodiment of the present invention, the target operation event includes at least one of network element version upgrade, network parameter adjustment, load balancing, energy saving setting, and neighbor cell adjustment.
In an embodiment of the present invention, the target indicator event includes at least one of a decrease in handover success rate, an increase in call drop rate, a decrease in access success rate, traffic channel congestion, a decrease in voice quality, and a decrease in data traffic quality.
The invention has the beneficial effects that:
the invention provides a method and a device for analyzing performance indexes of a communication network, which are used for establishing an operation event library and an index event library, wherein the operation event library comprises target operation events to be analyzed; the index event library comprises target index events to be analyzed; then, recording a target operation event occurring in the operation event library and a target index event occurring in the index event library to obtain an event record table for statistics; calculating the confidence degrees of the target index event and the corresponding target operation event according to the obtained event record table; and finally, determining target operation events related to the target index events according to the obtained confidence degrees. By the scheme, the target operation event related to each target index event can be automatically calculated and analyzed based on the result of automatically counting the occurred events. Compared with the existing mode of judging through experience of operators, the method is more objective, not only has higher efficiency and better accuracy, but also can greatly reduce labor cost.
Drawings
Fig. 1 is a schematic flow chart of a method for analyzing performance indicators of a communication network according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a confidence level calculation method according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating a confidence level calculation method according to a first embodiment of the present invention;
fig. 4 is a schematic structural diagram of a communication network performance index analysis apparatus according to a second embodiment of the present invention.
Detailed Description
According to the invention, by establishing an event library, recording events occurring in the event library through an event record table, and calculating the confidence coefficient of an occurring target index event and a corresponding target operation event according to the obtained event record table; and finally, determining the target operation event associated with each target index event according to the obtained confidence, so that the generated events can be automatically counted, and the target operation event associated with each target index event can be automatically calculated and analyzed. Compared with the existing mode of judging through experience of operators, the method is more objective, higher in efficiency and better in accuracy. The present invention will be described in further detail with reference to the following detailed description and accompanying drawings.
The first embodiment is as follows:
referring to fig. 1, the method for analyzing performance index of communication network provided in this embodiment includes the following steps:
step 101: establishing an operation event library, wherein the operation event library comprises target operation events to be analyzed;
step 102: establishing an index event library, wherein the index event library comprises target index events to be analyzed;
step 103: recording a target operation event occurring in the operation event library and a target index event occurring in the index event library to obtain an event record table, wherein the event record table can be specifically represented by an operation log or an operation work order;
step 104: calculating the confidence degrees of the target index event and the corresponding target operation event according to the event record table;
step 105: and determining target operation events related to the target index events according to the obtained confidence degrees.
It should be understood that the creation of the operation event library in step 101 and the creation of the index event library in step 102 are not strictly time-series limited, and may be performed simultaneously or in steps. In this embodiment, when creating the operation event library, the rule for adding the target operation event to the operation event library may be flexibly set according to actual requirements, for example, an event which is concerned by a user or has a large influence on a service and may have a high degree of association is selected to construct the operation event library. The selected target operation event includes, but is not limited to, at least one of network element version upgrade, network parameter adjustment, load balancing, energy saving setting, neighbor cell adjustment, and the like. For example, after the version upgrade, the possibility of voice quality or data service quality degradation is high, and at this time, the version upgrade may be added to the operation event library. When creating the index event library, the adding rule of the added index event may also be flexibly set according to specific requirements, and the target index event added in this embodiment includes, but is not limited to, at least one of a handover success rate decrease, a call drop rate increase, an access success rate decrease, traffic channel congestion, a voice quality decrease, and a data traffic quality decrease. The occurrence of the target index event may define that the malignant index reaches a certain threshold, for example, for the handover success rate, when the value of the handover success rate is lower than a set success rate threshold, it indicates that a handover success rate reduction event occurs; for example, for the call drop rate, when the call drop rate is greater than the set call drop rate threshold, it indicates that a call drop rate increase event has occurred; the judgment rule for whether other index events occur is the same as above.
In this embodiment, a target operation event occurring in the operation event library and a target index event occurring in the index event library are recorded to obtain an event record table, which also includes setting the association model library, and when performing event statistics, an event occurrence record is 1, and an event non-occurrence record is 0. When the event occurrence conditions in the event library are counted, the counting can be performed according to a preset counting period, for example, 1 day. The statistical period in this embodiment can be flexibly set according to specific requirements. The larger the statistical period is, the more the number of the recorded occurrence events is, whereas the smaller the statistical period is, the less the number of the recorded occurrence events is.
In the above step 105, the target operation event associated with the target index event is determined according to the confidence of the occurring target index event and the corresponding target operation event. In this embodiment, the target operation event associated with the occurring target index event means that the confidence is greater than a preset confidence threshold, for example, 70%. The specific value of the confidence level threshold in this embodiment can be flexibly set according to specific situations. In this embodiment, the confidence degrees of the target index event and each target operation event may be directly calculated, or the support degree between the target index event and each target operation event may be calculated first, and the confidence degrees between the target index event and the target operation events that are screened out may be calculated after screening is performed according to the support degree.
For ease of understanding, the following is a brief description of the support and confidence levels.
The formula for the degree of Support (Support) is: support (a- > B) ═ p (au B). The support reveals the probability of the A event and the B event occurring simultaneously. If the probability of the event A and the event B occurring at the same time is small, the relationship between the event A and the event B is not large; if the A event and the B event occur very frequently at the same time, the A event and the B event are always related.
The formula for Confidence (Confidence) is: configence (a- > B) ═ P (a | B). The confidence reveals whether or how likely the B event will also occur when the a event occurs. If the confidence level is too low, it indicates that the occurrence of the A event is not correlated with the occurrence of the B event. And calculating the association degree of the index event and the operation event by utilizing the support degree and the confidence degree, so that the probability caused by which operation events when the index event occurs can be obtained.
The following two ways are respectively illustrated to calculate the confidence degrees of the occurred target index event and the corresponding target operation event according to the event record table, and further determine the associated target operation event:
referring to fig. 2, the first method includes the following steps:
step 201: when a certain occurring target index event is calculated, calculating the confidence degrees of the target index event and each target operation event;
step 202: selecting the confidence level with the maximum value from the obtained confidence levels of the target index events;
step 203: judging whether the selected maximum confidence value is greater than a preset confidence threshold, if so, turning to step 204; otherwise, go to step 205;
step 204: and judging that the target operation event corresponding to the confidence coefficient is associated with the target index event.
Step 205: and judging that the target operation event corresponding to the confidence coefficient is not associated with the target index event.
In the step 202, it is sufficient to select the confidence value greater than or equal to the preset confidence threshold instead of the maximum confidence value, and then determine whether the confidence value greater than or equal to the confidence threshold exists from the selected confidence values.
Referring to fig. 3, the process includes the following steps:
step 301: when a certain occurring target index event is calculated, the support degree of the target index event and each target operation event is calculated;
step 302: selecting a target operation event with the maximum support value of the target index event;
step 303: calculating the confidence degree of the target indication event and the target operation event with the maximum support value;
step 304: judging whether the obtained large confidence value is larger than a preset confidence threshold, if so, turning to step 305; otherwise, go to step 306;
step 305: and judging that the target operation event corresponding to the confidence coefficient is associated with the target index event.
Step 306: and judging that the target operation event corresponding to the confidence coefficient is not associated with the target index event.
In the above step 302, instead of selecting the highest support value, the support value may be selected to be greater than or equal to the preset support threshold, and then the confidence value of the selected target operation event is calculated, and the determination of the step 304 is performed.
For a better understanding of the present invention, reference is made to the following description in conjunction with two specific examples.
Assume that the currently obtained event record table is shown in table one below:
watch 1
| ID | Network element version upgrade X | Adjacent cell adjustment Y | Drop of access success rate Z |
| 1 | 1 | 1 | 0 |
| 2 | 0 | 0 | 1 |
| 3 | 0 | 1 | 0 |
| 4 | 0 | 1 | 1 |
| 5 | 1 | 0 | 1 |
The first table above assumes that the target operation event in the operation event library is network element upgrade and neighbor cell adjustment, and the target index event in the index event library is access success rate reduction. The ID records events that occur at different times, where 1 is event occurrence and 0 is event non-occurrence.
In the above table i, the upgrade X of the element version appears in the transactions 1 and 5, the access success rate decreases Z and appears in the transactions 2, 4 and 5, the intersection X ^ Y of X and Z is 1, the transaction number D is 5, and the support (X ^ Y)/D is 0.2; the confidence coefficient of Z and X (X ^ Y)/X is 0.50;
adjusting Y to appear in affairs 1, 3 and 4, decreasing the access success rate and appearing in affairs 2, 4 and 5, the intersection Y ^ Z of Y and Z is 1, the affair frequency D is 5, and the support degree (Y ^ Z)/D is 0.2; y is 3, and confidence (Y ^ Z)/Y is 0.33.
As can be seen from the above table, the association degree between the index event Z and the operation event X is 50%, the association degree between the index event Z and the operation event Y is 33%, and the association degree between the network element version upgrade event X and the access success rate lowering event Z is higher, so that the probability of lowering the access success rate due to the operation is higher.
Assuming that within the statistical period, the change of the first table above becomes the second table below, namely, there is an index deterioration event:
watch two
At this time, in the second table above, the upgrade X of the element version appears in the transactions 1, 5, and 6, the access success rate decreases Z and appears in the transactions 2, 4, 5, and 6, the intersection X ^ Y of X and Z is 2, the transaction number D is 6, and the support degree (X ^ Y)/D is 0.33; the confidence coefficient of Z and X (X ^ Y)/X is 0.67;
adjusting Y to appear in affairs 1, 3 and 4, decreasing the access success rate and appearing in affairs 2, 4, 5 and 6, the intersection Y ^ Z of Y and Z is 1, the number of affairs D is 6, and the support degree (Y ^ Z)/D is 0.17; y is 3, and confidence (Y ^ Z)/Y is 0.33.
As can be seen from the above table, the support of the index event Z and the operation event X is increased to 33%, and the support of the index event Z and the operation event Y is decreased to 17%. The confidence (i.e. the degree of association) between the index event Z and the operation event X is raised to 67%, the confidence (i.e. the degree of association) between the index event Z and the operation event Y is still 33%, and the degree of association between the network element version upgrading event X and the access success rate lowering event Z is higher, so that the probability of the access success rate lowering caused by the operation is higher.
Therefore, in the statistical period, as time goes by, the records of the target operation events and the target index events in the relevance model library are more and more, and the calculated relevance between the target operation events and the target index events is more and more accurate. Some operations with the highest correlation degree can be found through a certain index deterioration event, and the reason of the deterioration of the communication network performance index can be found to the greatest extent through analyzing the operations.
Example two:
referring to fig. 4, the present invention provides a communication network performance index analyzing apparatus, which may be disposed in any PC or server, and specifically includes:
the operation event library establishing module 1 is used for establishing an operation event library, and the operation event library comprises target operation events to be analyzed;
the index event library establishing module 2 is used for establishing an index event library, and the index event library comprises target index events to be analyzed;
the event recording module 3 is used for recording a target operation event occurring in the operation event library and a target index event occurring in the index event library to obtain an event recording table;
the calculation module 4 is used for calculating the confidence degrees of the target index event and the corresponding target operation event according to the event record table;
and the analysis module 5 is used for determining target operation events related to the target index events according to the obtained confidence degrees.
In this embodiment, when the operation event library creating module 1 creates the operation event library, the rule for adding the target operation event to the operation event library may be flexibly set according to the actual requirement, for example, an event which is concerned by the user or has a large influence on the service and may have a high degree of association is selected to create the operation event library. The selected target operation event includes, but is not limited to, at least one of network element version upgrade, network parameter adjustment, load balancing, energy saving setting, neighbor cell adjustment, and the like.
In this embodiment, when the index event library establishing module 2 establishes the index event library, the adding rule of the added index event may also be flexibly set according to specific requirements, and the target index event added in this embodiment includes, but is not limited to, at least one of a decrease in handover success rate, an increase in call drop rate, a decrease in access success rate, congestion of a traffic channel, a decrease in voice quality, and a decrease in data traffic quality. The occurrence of the target indicator event may define that the malignant indicator reaches a certain threshold, for example, for the handover success rate, when the value of the handover success rate is lower than the set success rate threshold, it indicates that a handover success rate lowering event has occurred.
The event recording module 3 is configured to implement a correlation model library, and when performing event statistics, an event occurrence record is 1, and an event non-occurrence record is 0. When the event occurrence conditions in the event library are counted, the counting can be performed according to a preset counting period, for example, 1 day or 1 worship. The statistical period in this embodiment can be flexibly set according to specific requirements. The larger the statistical period is, the more the number of the recorded occurrence events is, whereas the smaller the statistical period is, the less the number of the recorded occurrence events is.
In this embodiment, the confidence degrees of the target index event and each target operation event may be directly calculated, or the support degree between the target index event and each target operation event may be calculated first, and the confidence degrees between the target index event and the target operation events that have been screened and screened may be calculated after screening according to the support degree. The above two modes are described below by way of example.
In the first mode:
the calculation module 4 includes:
the first calculation submodule is used for calculating the confidence degrees of a certain occurring target index event and each target operation event when the certain occurring target index event is calculated;
the analysis module 5 includes:
the confidence degree selecting submodule is used for selecting the confidence degree value with the maximum value from the obtained confidence degrees of a certain occurring target index event when the calculating module 4 comprises a first calculating submodule;
and the first judgment submodule is used for judging whether the selected maximum confidence value is greater than a preset confidence threshold, and if so, judging that the target operation event corresponding to the confidence is associated with the target index event.
The confidence degree selecting submodule does not select the maximum confidence degree, the confidence degree value is selected to be larger than or equal to the preset confidence degree threshold value, and then the first judging submodule judges whether the confidence degree value is larger than or equal to the confidence degree threshold value from the selected confidence degree value.
In the second embodiment:
the calculation module 4 includes:
the support degree operator module is used for calculating the support degree of a target index event and each target operation event when calculating the target index event;
the support degree selection submodule is used for selecting a target operation event with the maximum support degree value of the target index event;
and the second calculation submodule is used for calculating the confidence degree of the target indication event and the target operation event with the maximum support value.
The analysis module 5 includes a second determination sub-module, configured to determine whether the obtained confidence value is greater than a preset confidence threshold when the calculation module 4 includes the second calculation sub-module, and if so, determine that the target operation event corresponding to the confidence is associated with the target indicator event.
The support degree selection submodule does not select the support degree with the maximum value, but selects the support degree with the support degree value larger than or equal to the preset support degree threshold value, then the second calculation submodule calculates the confidence value of the selected target operation event, and then the second judgment submodule judges the confidence value.
For a better understanding of the invention, the invention is further illustrated below in connection with two scenarios.
Scene one:
the communication network performance index analysis device monitors that the wireless connection rate of the network reaches a lower limit threshold value and then analyzes which operation may cause the wireless connection rate.
After the wireless access rate reaches the lower threshold value every time, checking which base station cells have the wireless access rate reaching the lower threshold value, then obtaining relevant events within 1 day from an operation log or an operation work order, taking the operation performed on the base stations as operation events, recording the events as 1, and otherwise, recording the events as 0. And finally, selecting an event set with the highest TOPN support degree to carry out confidence coefficient calculation, wherein the set confidence coefficient threshold (namely the minimum confidence coefficient) is 70%, and then calculating the relevance degree of each operation under the condition that the wireless call completing rate reaches the lower limit threshold. Above 70%, it is considered that this operation results in a very high probability that the radio access rate reaches the lower threshold.
Scene two:
the communication network performance index analysis device analyzes which operation may cause after monitoring that the service call drop rate of the network exceeds an important threshold of 0.04.
After the service call drop rate exceeds the important threshold 0.04 every time, checking which base stations have the service call drop rate exceeding the important threshold 0.04, then obtaining relevant events within 1 day from an operation log or an operation work order, taking the operation performed on the base stations or the relevant RNC controllers as operation events, and recording the events as 1, otherwise, the events are 0. And finally, selecting a TOPN event set with the maximum support degree to carry out confidence coefficient calculation, wherein the set confidence coefficient threshold (namely the minimum confidence coefficient) is 70%, and then calculating the association degree of each operation under the condition that the service call drop rate exceeds an important threshold of 0.04. Above 70% it is considered that this operation results in a very high probability that the traffic drop rate exceeds the important threshold of 0.04.
It will be apparent to those skilled in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented in program code executable by a computing device, such that they may be stored on a storage medium (ROM/RAM, magnetic disk, optical disk) and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The foregoing is a more detailed description of the present invention that is presented in conjunction with specific embodiments, and the practice of the invention is not to be considered limited to those descriptions. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (10)
1. A method for analyzing performance index of communication network is characterized in that the method comprises the following steps:
establishing an operation event library, wherein the operation event library comprises target operation events to be analyzed; the operation event library is constructed according to the user requirement or the event with high business influence degree or high correlation degree with the target index event;
establishing an index event library, wherein the index event library comprises target index events to be analyzed;
recording a target operation event occurring in an operation event library and a target index event occurring in the index event library to obtain an event record table;
calculating the confidence degrees of the target index event and the corresponding target operation event according to the event record table;
and determining target operation events related to the target index events according to the obtained confidence degrees.
2. The method of claim 1, wherein calculating the confidence level of an occurring indicator event and a corresponding target operational event from the event log table comprises any one of:
the first method is as follows: calculating the confidence of a certain occurring target index event and each target operation event;
the second method comprises the following steps: calculating the support degree of a target index event and each target operation event when the target index event occurs;
selecting a target operation event with the maximum support value of the target index event;
and calculating the confidence degree of the target index event and the target operation event with the maximum support value.
3. The method of claim 2, wherein determining a target operational event associated with each target indicator event that occurs based on the derived confidence level comprises:
when the mode I is adopted, aiming at a certain occurring target index event, selecting the confidence coefficient with the maximum value from the obtained confidence coefficients of the target index event;
judging whether the selected maximum confidence value is greater than a preset confidence threshold, if so, judging that the target operation event corresponding to the confidence is associated with the target index event;
when the second mode is adopted, whether the obtained confidence value is greater than a preset confidence threshold or not is judged for a certain occurring target index event, and if yes, the target operation event corresponding to the confidence is judged to be associated with the target index event.
4. The method for analyzing performance index of communication network as claimed in any of claims 1 to 3, wherein the target operation event includes at least one of network element version upgrade, network parameter adjustment, load balancing, energy saving setting, and neighbor cell adjustment.
5. A method for performance indicator analysis in a communication network according to any of claims 1-3, wherein the target indicator events comprise at least one of handover success rate decrease, call drop rate increase, access success rate decrease, traffic channel congestion, voice quality decrease, data traffic quality decrease.
6. An apparatus for analyzing a performance index of a communication network, comprising:
the operation event library establishing module is used for establishing an operation event library, and the operation event library comprises target operation events to be analyzed; the operation event library is constructed according to the user requirement or the event with high business influence degree or high correlation degree with the target index event;
the system comprises an index event library establishing module, a target analysis module and a target analysis module, wherein the index event library establishing module is used for establishing an index event library, and the index event library comprises target index events to be analyzed;
the event recording module is used for recording a target operation event occurring in the operation event library and a target index event occurring in the index event library to obtain an event recording table;
the calculation module is used for calculating the confidence degrees of the target index event and the corresponding target operation event according to the event record table;
and the analysis module is used for determining target operation events related to the target index events according to the obtained confidence degrees.
7. The communication network performance indicator analysis device of claim 6, wherein the calculation module comprises:
the first calculation submodule is used for calculating the confidence degrees of a certain occurring target index event and each target operation event;
or comprises the following steps:
the support degree operator module is used for calculating the support degree of a certain target index event and each target operation event when the target index event occurs;
the support degree selection submodule is used for selecting a target operation event with the maximum support degree value of the target index event;
and the second calculation submodule is used for calculating the confidence degree of the target index event and the target operation event with the maximum support value.
8. The communication network performance indicator analysis device of claim 7, wherein the analysis module comprises:
the confidence degree selection submodule is used for selecting the confidence degree value with the maximum value from the obtained confidence degrees of a certain occurring target index event when the calculation module comprises the first calculation submodule;
the first judgment submodule is used for judging whether the selected maximum confidence value is greater than a preset confidence threshold, if so, judging that a target operation event corresponding to the confidence is associated with the target index event;
or the like, or, alternatively,
the analysis module comprises a second judgment submodule for judging whether the obtained confidence value is greater than a preset confidence threshold when the calculation module comprises the second calculation submodule, and if so, judging that the target operation event corresponding to the confidence is associated with the target index event.
9. The apparatus according to any of claims 6-8, wherein the target operation event comprises at least one of a network element version upgrade, a network parameter adjustment, a load balancing, an energy saving setting, and a neighbor cell adjustment.
10. The communication network performance indicator analysis device of any of claims 6-8, wherein the target indicator event comprises at least one of a handover success rate decrease, a dropped call rate increase, an access success rate decrease, traffic channel congestion, a voice quality decrease, a data traffic quality decrease.
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